Time: 6.- 17.7.2020, contact lessons are held from Monday to Friday 9:00-12:15
Place: Xamk, Mikkeli Campus
Extent: 3 ECTS credits
Number of study places: 5
Target group: All that are interested in this subject
Required previous skills: None
Lecturer: Dr. Laura J. White, USA

This course is a part of International Summer School in Mikkeli. Join the group of students from all over the world!

More info on Summer School and the courses is available here.

Credited at Xamk in degree: All Bachelor degrees at Xamk
Enrolment by: 31 May 2020
Price:  EUR 36 or semester fee EUR 175

Please, notice that the fee for one semester will not be refunded if the combined fees for your chosen studies remain below EUR 175 or you cancel your studies.

Please notice, that
Xamk degree students cannot enrol on OUAS courses.

Learning outcomes:

  • Describe primary concepts related to AI
  • Identify and explain relationships between AI and strongly related disciplines
  • Discuss the history of AI
  • Evaluate programming languages used in AI
  • Solve search and planning problems with perfect information
  • Formulate a real-world problem as a search problem
  • Formulate a simple real-world game problem as a game tree
  • Use searching to solve problems with uncertain information
  • Use odds and probabilities to solve AI problems
  • Solve problems using Bayes rule and Bayes naive classification
  • Define machine learning
  • Describe how machine learning is used to solve AI problems
  • Use the nearest neighbor classifier technique to predict user behavior
  • Describe characteristics of decision trees in machine learning
  • Solve machine learning types of problems using linear and logistic regression
  • Define neural networks
  • Explain how neural networks are used to solve AI problems
  • Describe how perception is used in AI problems
  • Evaluate the relationship between robotics and AI
  • Discuss the philosophy and the future of AI

Contents and methods:

  • Introduction to AI
  • Problem Solving with AI
  • Searching and Probabilistic Reasoning
  • Machine Learning
  • Neural Networks
  • Perception
  • Robotics
  • Philosophy of and the future of AI

Study material:
Provided by the lecturer.

100% attendance is compulsory. Course grade will be derived 30% from grades on individual and team exercises, and 70% from grade on final exam. 100% attendance is required to take the final exam and to take a resit exam. A minimum score of 40% on the final exam is required to pass this course.


A brief cv of the lecturer:

Lives in California, USA

Work History

  • 2015-Present Professor Emeritus, University of West Florida
  • 1992-2015 Associate Professor,      University of West Florida
  • 1972-1992 U.S. Navy
  • 1970-1972 Veterinary Assistant


  • 1984 BS Computer Engineering, University of New Mexico
  • 1989 MS Computer Science/Software Engineering, Navy Postgraduate School
  • 2005 PhD Instructional Design, Capella University

Transcript of records will be delivered by request
 – in paper form for those who have their home address in Finland
 – by email in PDF form for those who have their home address in some other country.

Finnish credits are fully compatible with the ECTS.

Additional information on enrolment:
Open University of Applied Sciences office, email openstudies@xamk.fi.

Terms of cancellation: 
You can cancel your enrolment free of charge 14 days before the course starts. If you have not cancelled by the due date, we will charge the full cost of the training. Cancellation by email to openstudies@xamk.fi.

You'll receive an invitation by email to this course approx. one week before the course starts.